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AI Trading Agents
Build, backtest & deploy autonomous agents that research and execute trades
GuidesBest Repos
The top open-source projects for building & backtesting agents, curated
10+ reposAI Platforms
Using Claude, ChatGPT & LLMs for strategy research and code generation
4 guidesTrading Strategies
Trend following, momentum, breakouts & mean reversion — and how to wire each into an agent
5 strategiesGuides
Plain-English explainers on how AI trading agents work end to end
GuidesBuild Log
Notes and findings from building and backtesting trading agents
BlogTop Repos for Building Agents
TradingAgents
A full "trading firm" of LLM agents that debate to a decision. ~89k★ — the reference architecture.
ai-hedge-fund
Agents modeled on famous investors. ~61k★ and the most approachable codebase to read first.
FinRL
The standard "train → backtest → trade" framework for RL trading agents. ~15.5k★.
NautilusTrader & vectorbt
Production-grade execution and lightning-fast research backtests — test before you deploy.
Build Your First Agent
Build Your First AI Trading Agent
LLM selection, framework choices, Alpaca paper trading, and the agent loop — from zero to running.
Backtesting AI Trading Agents
How to test an agent honestly — avoiding the overfitting traps that wreck live performance.
Connecting Agents to Broker APIs
Alpaca, Interactive Brokers, Coinbase — paper trading, execution, and mandatory safety mechanisms.
Using Claude for Trading
Strategy research, Python code generation, and structured market reasoning with LLMs.
Strategies to Automate
This site is for educational purposes only and does not constitute financial advice. Automated trading carries substantial risk. Backtest and paper-trade thoroughly; past performance is not indicative of future results.